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Extended Kalman filter for object tracking in modified spherical coordinates (MSC)

The `trackingMSCEKF`

object represents an extended Kalman filter
(EKF) for object tracking in modified spherical coordinates (MSC) using angle-only
measurements from a single observer. Use the filter to predict the future location of an
object in the MSC frame or associate multiple object detections with their tracks. You can
specify the observer maneuver or acceleration required by the state-transition functions
(`@constantvelmsc`

and `@constantvelmscjac`

) by using the
`ObserverInput`

property.

The following properties are fixed for the `trackingMSCEKF`

object:

`StateTransitionFcn`

-`@constvelmsc`

`StateTransitionJacobianFcn`

-`@constvelmscjac`

`MeasurementFcn`

-`@cvmeasmsc`

`MeasurementJacobianFcn`

-`@cvmeasmscjac`

`HasAdditiveProcessNoise`

-`false`

`HasAdditiveMeasurementNoise`

-`true`

`mscekf = trackingMSCEKF`

`mscekf = trackingMSCEKF(Name,Value)`

returns an
extended Kalman filter to use the MSC state-transition and measurement functions with
object trackers. The default `mscekf`

= trackingMSCEKF`State`

implies a static target at 1
meter from the observer at zero azimuth and elevation.

specifies the properties of the filter using one or more `mscekf`

= trackingMSCEKF(Name,Value)`Name,Value`

pair arguments. Any unspecified properties take default values.

`predict` | Predict state and state estimation error covariance |

`correct` | Correct state and state estimation error covariance |

`correctjpda` | Correct state and state estimation error covariance using JPDA |

`distance` | Distances between measurements and predicted measurements |

`residual` | Measurement residual and residual noise |

`clone` | Copy filter for object tracking |

`initialize` | Initialize state and covariance of filter |

`trackingCKF`

| `trackingEKF`

| `trackingGSF`

| `trackingIMM`

| `trackingPF`